{"id":"W4379208409","doi":"10.1101/2023.06.01.543292","title":"Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Structural Genomics Consortium; Montreal Neurological Institute and Hospital","funders":"National Institute on Aging; Genentech; Canadian Institutes of Health Research; Innovative Medicines Initiative; Mitacs; Motor Neurone Disease Association; Ontario Genomics Institute; Government of Canada; Merck KGaA; Ontario Genomics; Genome Canada; Medical Research Council; Bayer; ALS Society of Canada; McGill University; European Federation of Pharmaceutical Industries and Associations; Emory University; Bristol-Myers Squibb; Pfizer; ALS Association; Michael J. Fox Foundation for Parkinson's Research","keywords":"Antibody; Polyclonal antibodies; Proteome; Monoclonal antibody; Antibody Repertoire; Computational biology; Computer science; Biology; Immunology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01553263,0.002523772,0.001408157,0.002912824,0.001284438,0.002440823,0.001749747,0.001898877,0.003358943],"category_scores_gemma":[0.01745175,0.00096598,0.001550383,0.001708041,0.001454248,0.001323853,0.002094306,0.002505058,0.003689078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225249,"about_ca_system_score_gemma":0.001653465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001641509,"about_ca_topic_score_gemma":0.002220523,"domain_scores_codex":[0.9841229,0.003320802,0.001533053,0.003142711,0.007196214,0.000684179],"domain_scores_gemma":[0.9883235,0.002651612,0.001238641,0.002394666,0.005128549,0.0002630632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002239483,0.0004448009,0.006039317,0.0005761253,0.0001558726,0.0001103463,0.0003574505,0.00159773,0.9382477,0.001215724,0.002140628,0.04889039],"study_design_scores_gemma":[0.00003484487,0.001338326,0.01525818,0.0002412822,0.000216044,0.0003449852,0.000160186,0.01029833,0.9410727,0.001174795,0.02975714,0.0001031264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.257441,0.009299316,0.7051437,0.001308711,0.001409286,0.004067921,0.00353549,0.005871556,0.011923],"genre_scores_gemma":[0.3587663,0.006009888,0.6108593,0.001767052,0.0003438184,0.005945723,0.006554235,0.001491797,0.008261836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01553263,"threshold_uncertainty_score":0.08214539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06939039209198877,"score_gpt":0.3688292214780076,"score_spread":0.2994388293860188,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}